Systems and Methods for Data Application Linkages and Decommissioning in a Distributed Network

Example embodiments of the present disclosure relate generally to distributed networks and, more particularly, to systems and methods for data application linkages and decommissioning in these network implementations.

Electronic systems, communication systems, and/or other distributed networks may be formed of various data entities (e.g., computing devices, server devices, and/or the like) that are associated with a plurality of applications, operations, etc. In some instances, these data entities may define various interdependencies in which the operation of a data entity is impacted by the operation of other applications. Applicant has identified a number of deficiencies and problems associated with conventional systems and associated methods. Through applied effort, ingenuity, and innovation, many of these identified problems have been solved by developing solutions that are included in embodiments of the present disclosure, many examples of which are described in detail herein.

Systems, methods, and computer program products are provided herein for data application linkages and decommissioning in a distributed network. In one aspect, a system for dynamic data server fault steering in distributed networks may include at least one non-transitory storage device and at least one processor coupled to the at least one non-transitory storage device. The processor may be configured to identify a data application that is associated with a distributed network formed of a plurality of data entities and determine one or more data dependencies associated with the identified data application. The one or more data dependencies may include data entities whose operation is at least partially impacted by the identified data application. The processor may be further configured to determine an identification object for the data application where the identification object is configured to uniquely identify the data application and assign the identification object to each of the data entities associated with data dependencies.

In some embodiments, in determining an identification object for the data application, the at least one processor is further configured to determine an absence of an existing identification object for the data application and generate a new identification object for the data application.

In some embodiments, the at least one processor may be further configured to determine a change in the one or more data dependencies of at least a first data entity of the distributed network that is associated with the identified data application and dissociate the identification object from the first data entity.

In some embodiments, the at least one processor may be further configured to determine a new data dependency between the data application and a first data entity of the distributed network and assign the identification object to the first data entity.

In some embodiments, the at least one processor may be further configured to iteratively determine one or more data dependencies associated with the identified data application, iteratively assign the identification object to data entities having one or more data dependencies associated with the identified data application, and iteratively dissociate the identification object from data entities no longer having one or more data dependencies associated with the identified data application.

In some embodiments, the at least one processor may be further configured to receive a decommission request for the data application and determine one or more dependent data entities, wherein each of the dependent data entities are assigned the identification token of the data application.

In some further embodiments, the at least one processor may be further configured to decommission the data application and each of the dependent data entities.

In other further embodiments, the at least one processor may be further configured to decommission the data application and dissociate the identification object from each of the dependent data entities. In such an embodiment, the at least one processor may be further configured to expunge the identification object from the distributed network formed of the plurality of data entities.

In any embodiment, the at least one processor may be further configured to deploy a trained machine learning (ML) model on the data entities forming the distributed network to determine the one or more data dependencies associated with the identified data application.

In another aspect, a computer program for data application linkages and decommissioning in a distributed network is provided. The computer program product may include a non-transitory computer-readable medium including code that, when executed, causes an apparatus to identify a data application, wherein the data application is associated with a distributed network formed of a plurality of data entities; determine one or more data dependencies associated with the identified data application, wherein the one or more data dependencies include data entities of the distributed network whose operation is at least partially impacted by the identified data application; determine an identification object for the data application, wherein the identification object is configured to uniquely identify the data application; and assign the identification object to each of the data entities associated with the one or more data dependencies.

In another aspect, a method for data application linkages and decommissioning in a distributed network is provided. The method may include identifying a data application, wherein the data application is associated with a distributed network formed of a plurality of data entities; determining one or more data dependencies associated with the identified data application, wherein the one or more data dependencies include data entities of the distributed network whose operation is at least partially impacted by the identified data application; determining an identification object for the data application, wherein the identification object is configured to uniquely identify the data application; and assigning the identification object to each of the data entities associated with the one or more data dependencies.

The above summary is provided merely for purposes of summarizing some example embodiments to provide a basic understanding of some aspects of the present disclosure. Accordingly, it will be appreciated that the above-described embodiments are merely examples and should not be construed to narrow the scope or spirit of the disclosure in any way. It will be appreciated that the scope of the present disclosure encompasses many potential embodiments in addition to those here summarized, some of which will be further described below. The features, functions, and advantages that are described herein may be achieved independently in various embodiments of the present disclosure or may be combined with yet other embodiments.

Embodiments of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all, embodiments of the present disclosure are shown. Indeed, the present disclosure may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Where possible, any terms expressed in the singular form herein are meant to also include the plural form and vice versa, unless explicitly stated otherwise. Also, as used herein, the term “a” and/or “an” shall mean “one or more,” even though the phrase “one or more” is also used herein. Furthermore, when it is said herein that something is “based on” something else, it may be based on one or more other things as well. In other words, unless expressly indicated otherwise, as used herein “based on” means “based at least in part on” or “based at least partially on.” Like numbers refer to like elements throughout.

As used herein, an “entity” may be any institution employing information technology resources and particularly technology infrastructure configured for processing large amounts of data. Typically, this data may be related to the people who work for the organization, its products or services, the customers or any other aspect of the operations of the organization. As such, the entity may be any institution, group, association, financial institution, establishment, company, union, authority or the like, employing information technology resources for processing large amounts of data.

As described herein, a “user” may be an individual associated with or who otherwise interacts with an entity. As such, in some embodiments, the user may be an individual having past relationships, current relationships, and/or potential future relationships with an entity. In some embodiments, the user may be an employee (e.g., an associate, a project manager, an IT specialist, a manager, an administrator, an internal operations analyst, or the like) of the entity or enterprises affiliated with the entity. In some embodiments, the user may be a customer (e.g., individual, business, etc.) that transacts with the entity or enterprises associated with the entity. In some embodiments, the “user(s)” described herein may refer to a user, system, device, etc. associated with a third party service provider.

As used herein, a “user interface” may be a point of human-computer interaction and communication in a device that allows a user to input information, such as commands or data, into a device, or that allows the device to output information to the user. For example, the user interface includes a graphical user interface (GUI) or an interface to input computer-executable instructions that direct a processor to carry out specific functions. The user interface typically employs certain input and output devices such as a display, mouse, keyboard, button, touchpad, touch screen, microphone, speaker, LED, light, joystick, switch, buzzer, bell, and/or other user input/output device for communicating with one or more users. The present disclosure contemplates that the arrangement, presentation, organization, etc. of the user interfaces described herein may vary based upon the intended application of the system.

As used herein, an “engine” or “module” may refer to core elements of an application, or part of an application that serves as a foundation for a larger piece of software and drives the functionality of the software. In some embodiments, an engine or module may be self-contained, but externally-controllable code that encapsulates powerful logic designed to perform or execute a specific type of function. In one aspect, an engine or module may be underlying source code that establishes file hierarchy, input and output methods, and how a specific part of an application interacts or communicates with other software and/or hardware. The specific components of an engine or module may vary based on the needs of the specific application as part of the larger piece of software. In some embodiments, an engine or module may be configured to retrieve resources created in other applications, which may then be ported into the engine for use during specific operational aspects of the engine. An engine or module may be configurable to be implemented within any general purpose computing system. In doing so, the engine may be configured to execute source code embedded therein to control specific features of the general purpose computing system to execute specific computing operations, thereby transforming the general purpose system into a specific purpose computing system.

It should also be understood that “operatively coupled,” “communicably coupled” and/or the like as used herein, means that the components may be formed integrally with each other, or may be formed separately and coupled together. Furthermore, the components may be formed directly to each other, or to each other with one or more components located between the components that are operatively coupled together. Furthermore, the components may be detachable from each other, or they may permanently coupled together. Furthermore, operatively coupled components may mean that the components retain at least some freedom of movement in one or more directions or may be rotated about an axis (e.g., rotationally coupled, pivotally coupled). Furthermore, “operatively coupled” may mean that components may be electronically connected and/or in fluid communication with one another.

As used herein, an “interaction” may refer to any communication between one or more users, one or more entities or institutions, one or more devices, nodes, clusters, or systems within the distributed computing environment described herein. For example, an interaction may refer to a transfer or transmission of data between devices, a system and an application, an accessing of stored data by one or more nodes of a computing cluster, a transmission of a requested task, or the like. As described hereinafter, an “interaction” between the system and one or more applications may be permissioned in that the ability for the system (e.g., one or more devices, subsystems, modules, etc.) to access a particular application may be controlled by permissions issued by this application.

As used herein, “determining” may encompass a variety of actions. For example, “determining” may include calculating, computing, processing, deriving, investigating, ascertaining, and/or the like. Furthermore, “determining” may also include receiving (e.g., receiving information), accessing (e.g., accessing data in a memory), and/or the like. Also, “determining” may include resolving, selecting, choosing, calculating, establishing, and/or the like. Determining may also include ascertaining that a parameter matches a criterion, including that a threshold has been met, passed, exceeded, etc.

As used herein, a “data entity” may refer to any device, application, network component, middleware component, database, storage device, and/or the like that form a distributed network as described herein. The present disclosure contemplates that any component, element, etc. that is associated with or leveraged by the distributed network may be considered a “data entity” for purposes of the data application linkage and decommissioning operations described herein. Furthermore, although described herein with reference to a data application to which other data entities may be linked (e.g., via a data dependency determination), the present disclosure contemplates that the example data application may also be considered a data entity for other data linking and decommissioning operations.

As described above, electronic systems, communication systems, and/or other distributed networks may be formed of various data entities (e.g., computing devices, server devices, and/or the like) that are associated with a plurality of applications, operations, etc. In some instances, these data entities may define various interdependencies in which the operation of a data entity is impacted by the operation of other applications. By way of a particular example, a distributed network, such as a network associated with an entity, may deploy various data applications in the distributed network or application environment. Once deployed, these data applications may be regularly changed, updated, replaced, etc. Furthermore, these data applications may include various dependencies with other applications, infrastructure components, and/or the like. Due to these dependencies, the decommissioning of an application may impact the operations of various other applications and infrastructure components forming the distributed network. Furthermore, the failure of traditional systems to properly identify these data dependencies during a decommissioning operation may result is security exposure for the dependent applications, components, etc. that are not properly decommissioned.

In order to solve these issues and others, embodiments of the present disclosure provide systems and methods for data application linkages and decommissioning in a distributed network. For example, the embodiments described herein may identify a data application, that is associated with a distributed network formed of a plurality of data entities and determine one or more data dependencies associated with the identified data application where the one or more data dependencies comprise data entities whose operation is at least partially impacted by the identified data application. These embodiments may further determine an identification object for the data application and assign the identification object to each of the data entities associated with the data dependencies. Thereafter, as part of a decommission request, the embodiments of the present disclosure may decommission the data application as detailed by the request but may further decommission each of the dependent data entities and/or dissociate the identification object from each of the dependent data entities. The system may further leverage machine learning (ML) model and artificial intelligence (AI) techniques to determined data dependencies and my further iteratively assign and dissociate identification objects based on modification to data dependencies during operation. In doing so, the embodiments of the present disclosure provide new mechanisms for determining data dependencies in distributed data environments so as to enable application decommissioning operations for linked data entities that were historically unavailable.

1 1 FIGS.A-C 1 FIG.A 1 FIG.A 100 100 100 130 140 110 130 140 100 100 130 illustrate technical components of an exemplary distributed computing environment for data application linkages and decommissioning in a distributed network, in accordance with one or more embodiments of the present disclosure. As shown in, the distributed computing environmentor distributed networkcontemplated herein may include a system, an end-point device(s), and a networkover which the systemand end-point device(s)communicate therebetween.illustrates only one example of an embodiment of the distributed computing environment, and it will be appreciated that in other embodiments one or more of the systems, devices, and/or servers may be combined into a single system, device, or server, or be made up of multiple systems, devices, or servers. Also, the distributed computing environmentmay include multiple systems, the same or similar to system, with each system providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system).

130 140 140 130 130 140 130 140 110 130 110 In some embodiments, the systemand the end-point device(s)may define a client-server relationship in which the end-point device(s)are remote devices that request and receive service from a centralized server (e.g., the system). In some other embodiments, the systemand the end-point device(s)may have a peer-to-peer relationship in which the systemand the end-point device(s)have the same abilities to use the resources available on the network. As opposed to relying upon a central server (e.g., system) that acts as the shared drive, each device that is connected to the networkacts as the server for the files stored thereon.

130 The systemmay represent various forms of servers, such as web servers, database servers, file server, or the like, various forms of digital computing devices, such as laptops, desktops, video recorders, audio/video players, radios, workstations, or the like, or any other auxiliary network devices, such as wearable devices, Internet-of-things devices, electronic kiosk devices, mainframes, or the like, or any combination of the aforementioned.

140 140 The end-point device(s)(e.g., data entities) may represent various forms of electronic devices, including user input devices such as personal digital assistants, cellular telephones, smartphones, laptops, desktops, and/or the like, merchant input devices such as point-of-sale (POS) devices, electronic payment kiosks, and/or the like, electronic telecommunications device (e.g., an automated teller machine (ATM)), and/or edge devices such as routers, routing switches, integrated access devices (IAD), and/or the like. As described hereinafter, in some embodiments, the end-point devicesmay be data entities that are linked with the subject data application described herein.

110 110 110 The networkmay be a distributed network that is spread over different networks. This provides a single data communication network that may be managed jointly or separately by each network. In addition to shared communication within the network, the distributed network may also support distributed processing. The networkmay be a form of digital communication network, such as a telecommunication network, a local area network (“LAN”), a wide area network (“WAN”), a global area network (“GAN”), the Internet, or any combination of the foregoing. The networkmay be secure and/or unsecure and may also include wireless and/or wired and/or optical interconnection technology.

100 100 130 It is to be understood that the structure of the distributed computing environment and its components, connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the embodiments of the present disclosure. In one example, the distributed computing environmentmay include more, fewer, or different components. In another example, some or all of the portions of the distributed computing environmentmay be combined into a single portion, or all of the portions of the systemmay be separated into two or more distinct portions.

1 FIG.B 1 FIG.B 130 130 102 104 116 110 130 108 104 112 114 110 102 104 108 110 112 102 130 illustrates an exemplary component-level structure of the system, in accordance with one or more embodiments of the present disclosure. As shown in, the systemmay include a processor, memory, input/output (I/O) device, and/or a storage device. The systemmay also include a high-speed interfaceconnecting to the memory, and a low-speed interfaceconnecting to low speed busand storage device. Each of the components,,,, andmay be operatively coupled to one another using various buses and may be mounted on a common motherboard or in other manners as appropriate. As described herein, the processormay include a number of subsystems to execute the portions of processes described herein. Each subsystem may be a self-contained component of a larger system (e.g., system) and capable of being configured to execute specialized processes as part of the larger system.

102 104 110 130 130 The processormay process instructions, such as instructions of an application that may perform the functions disclosed herein. These instructions may be stored in the memory(e.g., non-transitory storage device) or on the storage device, for execution within the systemusing any subsystems described herein. It is to be understood that the systemmay use, as appropriate, multiple processors, along with multiple memories, and/or I/O devices, to execute the processes described herein.

104 130 104 100 100 104 104 104 130 The memorystores information within the system. In one implementation, the memoryis a volatile memory unit or units, such as volatile random access memory (RAM) having a cache area for the temporary storage of information, such as a command, a current operating state of the distributed computing environment, an intended operating state of the distributed computing environment, instructions related to various methods and/or functionalities described herein, and/or the like. In another implementation, the memoryis a non-volatile memory unit or units. The memorymay also be another form of computer-readable medium, such as a magnetic or optical disk, which may be embedded and/or may be removable. The non-volatile memory may additionally or alternatively include an EEPROM, flash memory, and/or the like for storage of information such as instructions and/or data that may be read during execution of computer instructions. The memorymay store, recall, receive, transmit, and/or access various files and/or information used by the systemduring operation.

106 130 106 104 104 102 The storage devicemay be capable of providing mass storage for the system. In one aspect, the storage devicemay be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. A computer program product may be tangibly embodied in an information carrier. The computer program product may also contain instructions that, when executed, perform one or more methods, such as those described above. The information carrier may be a non-transitory computer-or machine-readable storage medium, such as the memory, the storage device, or memory on processor.

108 130 112 108 104 116 111 112 106 114 114 The high-speed interfacemanages bandwidth-intensive operations for the system, while the low speed controllermanages lower bandwidth-intensive operations. Such allocation of functions is exemplary only. In some embodiments, the high-speed interfaceis coupled to memory, input/output (I/O) device(e.g., through a graphics processor or accelerator), and/or to high-speed expansion ports, which may accept various expansion cards (not shown). In such an implementation, low-speed controlleris coupled to storage deviceand low-speed expansion port. The low-speed expansion port, which may include various communication ports (e.g., USB, Bluetooth, Ethernet, wireless Ethernet), may be coupled to one or more input/output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.

130 130 130 130 130 The systemmay be implemented in a number of different forms. For example, it may be implemented as a standard server, or multiple times in a group of such servers. Additionally, the systemmay also be implemented as part of a rack server system or a personal computer such as a laptop computer. Alternatively, components from systemmay be combined with one or more other same or similar systems and an entire systemmay be made up of multiple computing devices communicating with each other. As described herein, in some embodiments, the systemmay operate as the centralized server configured to perform the data application linkage and decommissioning operations described herein.

1 FIG.C 1 FIG.C 140 140 152 154 156 158 160 140 152 154 158 160 140 130 140 illustrates an exemplary component-level structure of the end-point device(s)(e.g., data entities described herein), in accordance with one or more embodiments of the present disclosure. As shown in, the end-point device(s)includes a processor, memory, an input/output device such as a display, a communication interface, and a transceiver, among other components. The end-point device(s)may also be provided with a storage device, such as a Microdrive or other device, to provide additional storage. Each of the components,,, and, are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate. As described above, the end-point devicesdescribed herein may be example data entities that form the distributed network. As such, the systemmay be communicably coupled with the data entities (e.g., end-point devices) so as to receive data transmissions from these devices that may, for example, be used for data dependency determination.

152 140 154 140 140 140 The processoris configured to execute instructions within the end-point device(s), including instructions stored in the memory, which in one embodiment includes the instructions of an application that may perform the functions disclosed herein, including certain logic, data processing, and data storing functions. The processor may be implemented as a chipset of chips that include separate and multiple analog and digital processors. The processor may be configured to provide, for example, for coordination of the other components of the end-point device(s), such as control of user interfaces, applications run by end-point device(s), and wireless communication by end-point device(s).

152 164 166 156 156 156 156 164 152 168 152 140 168 The processormay be configured to communicate with the user through control interfaceand display interfacecoupled to a display. The displaymay be, for example, a TFT LCD (Thin-Film-Transistor Liquid Crystal Display) or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology. The display interfacemay comprise appropriate circuitry and configured for driving the displayto present graphical and other information to a user (e.g., an actionable notification or the like). The control interfacemay receive commands from a user and convert them for submission to the processor. In addition, an external interfacemay be provided in communication with processor, so as to enable near area communication of end-point device(s)with other devices. External interfacemay provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.

154 140 154 140 140 140 140 The memorystores information within the end-point device(s). The memorymay be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory unit or units. Expansion memory may also be provided and connected to end-point device(s)through an expansion interface (not shown), which may include, for example, a SIMM (Single In Line Memory Module) card interface. Such expansion memory may provide extra storage space for end-point device(s)or may also store applications or other information therein. In some embodiments, expansion memory may include instructions to carry out or supplement the processes described above and may include secure information also. For example, expansion memory may be provided as a security module for end-point device(s)and may be programmed with instructions that permit secure use of end-point device(s). In addition, secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackable manner.

154 154 152 160 168 The memorymay include, for example, flash memory and/or NVRAM memory. In one aspect, a computer program product is tangibly embodied in an information carrier. The computer program product contains instructions that, when executed, perform one or more methods, such as those described herein. The information carrier is a computer-or machine-readable medium, such as the memory, expansion memory, memory on processor, or a propagated signal that may be received, for example, over transceiveror external interface.

140 130 110 130 140 130 130 130 140 130 140 In some embodiments, the user may use the end-point device(s)(e.g., data entities) to transmit and/or receive information or commands to and from the systemvia the network. Any communication between the systemand the end-point device(s)may be subject to an authentication protocol allowing the systemto maintain security by permitting only authenticated users (or processes) to access the protected resources of the system, which may include servers, databases, applications, and/or any of the components described herein. To this end, the systemmay trigger an authentication subsystem that may require the user (or process) to provide authentication credentials to determine whether the user (or process) is eligible to access the protected resources. Once the authentication credentials are validated and the user (or process) is authenticated, the authentication subsystem may provide the user (or process) with permissioned access to the protected resources. Similarly, the end-point device(s)may provide the system(or other client devices) permissioned access to the protected resources of the end-point device(s), which may include a GPS device, an image capturing component (e.g., camera), a microphone, and/or a speaker.

140 130 158 158 158 160 170 140 130 The end-point device(s)(e.g., data entities) may communicate with the systemthrough communication interface, which may include digital signal processing circuitry where necessary. Communication interfacemay provide for communications under various modes or protocols, such as the Internet Protocol (IP) suite (commonly known as TCP/IP). Protocols in the IP suite define end-to-end data handling methods for everything from packetizing, addressing and routing, to receiving. Broken down into layers, the IP suite includes the link layer, containing communication methods for data that remains within a single network segment (link); the Internet layer, providing internetworking between independent networks; the transport layer, handling host-to-host communication; and the application layer, providing process-to-process data exchange for applications. Each layer contains a stack of protocols used for communications. In addition, the communication interfacemay provide for communications under various telecommunications standards (2G, 3G, 4G, 5G, and/or the like) using their respective layered protocol stacks. These communications may occur through a transceiver, such as radio-frequency transceiver. In addition, short-range communication may occur, such as using a Bluetooth, Wi-Fi, or other such transceiver (not shown). In addition, GPS (Global Positioning System) receiver modulemay provide additional navigation—and location-related wireless data to end-point device(s), which may be used as appropriate by applications running thereon, and in some embodiments, one or more applications operating on the system.

140 162 162 140 140 130 100 130 140 The end-point device(s)(e.g., data entities) may also communicate audibly using audio codec, which may receive spoken information from a user and convert it to usable digital information. Audio codecmay likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of end-point device(s). Such sound may include sound from voice telephone calls, may include recorded sound (e.g., voice messages, music files, etc.) and may also include sound generated by one or more applications operating on the end-point device(s), and in some embodiments, one or more applications operating on the system. Various implementations of the distributed computing environment, including the systemand end-point device(s)(e.g., data entities), and techniques described here may be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof.

2 FIG. 2 FIG. 1 1 FIGS.A-C 200 130 140 102 152 illustrates a flowchart containing a series of operations for example data application linkages and decommissioning in a distributed network (e.g., method). The operations illustrated inmay, for example, be performed by, with the assistance of, and/or under the control of an apparatus (e.g., system, end-point devices(e.g., data entities), etc.), as described above. In this regard, performance of the operations may invoke one or more of the components described above with reference to(e.g., processor, processor, etc.).

202 130 130 140 130 110 130 140 130 130 As shown in operation, the systemmay be configured to identify a data application where the data application is associated with a distributed network formed of a plurality of data entities. As described above, the systemmay operate as a centralized server or other computing device that is communicably coupled with a plurality of data entities (e.g., end-point devices) forming a distributed network. The systemmay be configured to receive communications, such as over network, from the various data entities forming the distributed network. In some embodiments, the systemmay receive data transmissions from the data entities (e.g., end-point devices) periodically (e.g., according to a determined frequency) regardless of the applications, components, and/or any other data entity formed in the distributed network as described hereafter. Said differently, the systemmay routinely receive data transmission from the data entities with which it interacts that may be indicative of the relationship or dependencies between the applications and data entities in the distributed network. The systemmay be configured to identify an example data application via one or more of these periodic transmissions.

130 202 202 202 2 FIG. In other embodiments, the systemmay be configured to identify the data application at operationin response to the registration of a new application, data entity, etc. within the distributed network or other environment. By way of example, a data application may be new (e.g., originally presented or in a new use of the data application) to the distributed network, such that the implementation of the data application causes the linkage of the data application with one or more of the data entities forming the distributed network. This linkage, for example and as described further hereinafter, may relate to the data dependencies between the new application and the data entities forming the distributed network in that the operation of these data entities is at least partially impacted by the operation of the new data application. As such, the identification operation at operationinmay refer to an initial registration implementation of a data application in the distributed network. Although described herein with reference to an example data application, the identification at operationmay similarly refer to the initial implementation of a data entity that is subsequently linked to the example data application as described herein.

204 130 In some embodiments, as shown in operation, the systemmay be configured to deploy a trained machine learning (ML) model on the data entities forming the distributed network so as to determine the one or more data dependencies described hereinafter. The trained ML model may also refer to a mathematical model generated by machine learning algorithms based on training data (e.g., various feature sets of access permissions), to make predictions or decisions without being explicitly programmed to do so. The trained ML model may similarly represent what was learned by the selected machine learning algorithm and represent the rules, numbers, and any other algorithm-specific data structures required for decision-making. Selecting the right machine learning algorithm may depend on a number of different factors, such as the problem statement and the kind of output needed, type and size of the data, the available computational time, number of features and observations in the data, and/or the like. The trained ML model or algorithm may also refer to programs that are configured to self-adjust and perform better as they are exposed to more data. To this extent, the trained ML model or algorithm is also capable of adjusting its own parameters, based on previous performance in making prediction about a dataset.

The ML algorithms contemplated, described, and/or used herein (e.g., the trained ML model) may include supervised learning (e.g., using logistic regression, using back propagation neural networks, using random forests, decision trees, etc.), unsupervised learning (e.g., using an Apriori algorithm, using K-means clustering), semi-supervised learning, reinforcement learning (e.g., using a Q-learning algorithm, using temporal difference learning), and/or any other suitable machine learning model type. Each of these types of machine learning algorithms can implement any of one or more of a regression algorithm (e.g., ordinary least squares, logistic regression, stepwise regression, multivariate adaptive regression splines, locally estimated scatterplot smoothing, etc.), an instance-based method (e.g., k-nearest neighbor, learning vector quantization, self-organizing map, etc.), a regularization method (e.g., ridge regression, least absolute shrinkage and selection operator, elastic net, etc.), a decision tree learning method (e.g., classification and regression tree, iterative dichotomiser 3, C4.5, chi-squared automatic interaction detection, decision stump, random forest, multivariate adaptive regression splines, gradient boosting machines, etc.), a Bayesian method (e.g., naïve Bayes, averaged one-dependence estimators, Bayesian belief network, etc.), a kernel method (e.g., a support vector machine, a radial basis function, etc.), a clustering method (e.g., k-means clustering, expectation maximization, etc.), an associated rule learning algorithm (e.g., an Apriori algorithm, an Eclat algorithm, etc.), an artificial neural network model (e.g., a Perceptron method, a back-propagation method, a Hopfield network method, a self-organizing map method, a learning vector quantization method, etc.), a deep learning algorithm (e.g., a restricted Boltzmann machine, a deep belief network method, a convolution network method, a stacked auto-encoder method, etc.), a dimensionality reduction method (e.g., principal component analysis, partial least squares regression, Sammon mapping, multidimensional scaling, projection pursuit, etc.), an ensemble method (e.g., boosting, bootstrapped aggregation, AdaBoost, stacked generalization, gradient boosting machine method, random forest method, etc.), and/or the like.

The ML models may be trained using repeated execution cycles of experimentation, testing, and tuning to modify the performance of the ML algorithm and refine the results in preparation for deployment of those results for consumption or decision making. The ML models may be tuned by dynamically varying hyperparameters in each iteration (e.g., number of trees in a tree-based algorithm or the value of alpha in a linear algorithm), running the algorithm on the data again, and then comparing its performance on a validation set to determine which set of hyperparameters results in the most accurate model. The accuracy of the model is the measurement used to determine which set of hyperparameters is best at identifying relationships and patterns between variables in a dataset based on the input, or training data. A fully trained ML model is one whose hyperparameters are tuned and model accuracy maximized.

206 130 206 Thereafter, as shown in operation, the systemmay be configured to determine one or more data dependencies associated with the identified data application. As described above, the data application may be associated with, linked to, or otherwise implicated by various data entities that form the distributed network. By way of a non-limiting example, servers, network components, middleware components, databases, storage devices, certificate systems, access management systems, among others may use or otherwise be associated with the identified data application. As such, the one or more data dependencies determined at operationmay include or otherwise be associated with data entities whose operation is at least partially impacted by the identified data application. In some embodiments, the deployed ML models may operate to identify the existence of the association between the data application and the data entities forming the distributed network. In other embodiments, each data entity and/or data application that is used by the distributed network may explicitly define data dependencies as part of the initialization of these data entities and/or data applications as described hereinafter.

208 130 202 130 130 In some embodiments, as shown in operation, the systemmay be configured to determine an absence of an existing identification object for the data application and generate a new identification object for the data application. By way of example, in some embodiments, the data application identified at operationmay be new to the distributed network such that the data application lacks a mechanism for uniquely identifying the data application for data linkage and decommissioning operations. In such an embodiment, the systemmay generate a new identification object that uniquely identify the data application. The present disclosure contemplates that any mechanism for identification may be used in the generation of the identification object and that the identification object may include alphanumeric characters, encrypted identifier, tokenized identification, and/or the like based on the intended application of the systemand/or identified data application.

210 130 210 Thereafter, as shown in operation, the systemmay be configured to determine an identification object for the data application. As described above, the identification object may refer to any mechanism for uniquely identifying the data application within the distributed network. In some embodiments, as shown in operation, the determination may refer to the identification of an identification object that is already assigned or otherwise associated with the data application. For example, the identified data application may, as part of an initialization or registration operation, be assigned an identification object that uniquely identifies the data application within the distributed network. The present disclosure contemplates that the identified data application may be leveraged by any number of systems, networks, data entities, etc. that may be in the same or different computing environments. As such, in some embodiments, the data application may be assigned or associated with a plurality of identification objects that may, for example, be implementation specific.

210 130 130 130 130 3 4 FIGS.- Thereafter, as shown in operation, the systemmay be configured to assign the identification object to each of the data entities associated with the one or more data dependencies. By way of continued example, during the initialization or registration of a data entity, the systemmay assign the identification object to a data entity that is determined to have a data dependency with the data application. Similarly, the initialization or registration of a new data application may cause the identification object for the data application to be assigned to each of the data entities that have a data dependency with the data application. In some embodiments, as described hereinafter with reference to, the systemmay operate to iteratively determine the data dependencies associated with a particular data application, iteratively assign the identification object to data entities having one or more data dependencies associated with the identified data application, and iteratively dissociate the identification object from data entities no longer having one or more data dependencies associated with the identified data application. In doing so, the systemmay operate to dynamically modify the data dependency structure and associate linkages in a particular distributed network during live operation of the data application and associated data entities.

3 FIG. 3 FIG. 1 1 FIGS.A-C 300 130 140 102 152 illustrates a flowchart containing a series of operations for data dependency updating (e.g., method). The operations illustrated inmay, for example, be performed by, with the assistance of, and/or under the control of an apparatus (e.g., system, end-point devices(e.g., data entities), etc.), as described above. In this regard, performance of the operations may invoke one or more of the components described above with reference to(e.g., processor, processor, etc.).

302 130 As shown in operation, in some embodiments, the systemmay be configured to determine a change in the one or more data dependencies of at least a first data entity of the distributed network that is associated with the identified data application. As would be evident to one of ordinary skill in the art in light of the present disclosure, the data applications, data entities, and/or the like that form a distributed network may change. By way of a non-limiting example, a particular data entity may be replaced (e.g., upgraded, serviced, etc.), a particular data application may be replaced (e.g., upgraded, serviced, etc.), and/or the like, such that the data dependencies for a particular distributed network change. By way of example, the access permissions for a particular data entity may change such that that the particular data entity is no longer capable of accessing the identified data application. As such, the particular data entity that lacks access permission for the data application no longer should be linked (e.g., include a data dependency) with the data application. Although described herein with reference to data entity update, application replacement, access permission modification, and/or the like, the present disclosure contemplates that any change associated with the data application and/or the data entities may be used to modify the data dependencies between the components forming the distributed network.

304 130 130 130 130 130 2 FIG. 3 FIG. Thereafter, as shown in operation, the systemmay be configured to dissociate the identification object from the first data entity. By way of continued example, the data entities forming the distributed network and/or the data application may change such that the data dependencies between the data entities and the data application similarly change. In response to such a change, the systemmay operate to dissociate the identification object that uniquely identifies the data application from the first data entity (e.g., any example data entity that no longer includes a data dependency with the example data application). For example, the systemmay perform the reverse of the assigning of the identification object (e.g., as described in) by causing the identification token to be no longer assigned with the data entity. By way of a non-limiting example, the systemmay transmit instructions to the data entity that cause the identification token for the example data application to be removed from the data entity. The present disclosure contemplates that the systemmay leverage any technique, mechanism, etc. for causing the data entity to no longer be linked with the example data application without limitation. As illustrated, the present disclosure contemplates that the operations ofmay occur iteratively for each of the data entities that are within the distributed network so as to provide a dynamic mechanism for determining data dependencies and dissociating data entities with a data dependencies no longer exists.

4 FIG. 4 FIG. 1 1 FIGS.A-C 400 130 140 102 152 illustrates a flowchart containing a series of operations for new data dependency determinations (e.g., method). The operations illustrated inmay, for example, be performed by, with the assistance of, and/or under the control of an apparatus (e.g., system, end-point devices(e.g., server devices), etc.), as described above. In this regard, performance of the operations may invoke one or more of the components described above with reference to(e.g., processor, processor, etc.).

402 130 130 130 402 404 130 404 212 2 FIG. 4 FIG. As shown in operation, the systemmay be configured to determine a new data dependency between the data application and a first data entity of the distributed network. By way of continued example, the systemmay operate to dynamically determine or identify data entities of the distributed network that may be associated with the data application. By way of a non-limiting example, a new data entity (e.g., network component, middleware component, etc.) may be implemented by the distributed network. During the initialization or registration of this new data entity, the systemmay determine a data dependency between the new data entity and the data application. Although described herein with reference to a new data entity added to the distributed network, the present disclosure contemplates that operationmay similarly occur for existing data entities that were previously not dependent upon the example data application. By way of a non-limiting example, the functionality, access permission, and/or the like for an existing data entity may change such that the existing data entity is now associated with the example data application. Thereafter, as shown in operation, the systemmay be configured to assign the identification object to the first data entity, where the first data entity refers to any data entity that is newly associated or linked with the example data application. Operationmay occur similarly to operationinfor the example first data entity. As illustrated, the present disclosure contemplates that the operations ofmay occur iteratively for each of the data entities that are within the distributed network.

5 FIG. 5 FIG. 1 1 FIGS.A-C 500 130 140 102 152 illustrates a flowchart containing a series of operations for data application decommissioning (e.g., method). The operations illustrated inmay, for example, be performed by, with the assistance of, and/or under the control of an apparatus (e.g., system, end-point devices(e.g., server devices), etc.), as described above. In this regard, performance of the operations may invoke one or more of the components described above with reference to(e.g., processor, processor, etc.).

502 130 502 130 502 As shown in operation, the systemmay be configured to receive a decommission request for the data application. As described above, the distributed network of the present disclosure may employ various data applications, data entities, and/or the like the composition of which may, for example, change over time. By way of a non-limiting example, the data application described herein may be retired, upgraded, or otherwise removed from operation within the distributed network. As such, operationmay refer to instructions received or generated by the systemfor decommissioning the example data application. The present disclosure contemplates that the decommission request received at operationmay be associated with any reason for commissioning the data application without limitation.

504 130 504 130 130 130 504 2 FIG. Thereafter, as shown in operation, the systemmay be configured to determine one or more dependent data entities in the distributed network. As described above with reference to the operations of, each of the dependent data entities may be assigned the identification token of the example data application, such as during an initialization or registration process for the data application and/or data entity. As such, the determination of the dependent data entities at operationmay refer to an operation by the systemto identify each and every data entity within the distributed network that is assigned the identification object for the example data application. In some embodiments, the systemmay query one or more of the data entities in the distributed network to determine if the queried data entity is assigned the identification object. In other embodiments, the systemmay access a data repository or other data structure that stores data dependencies data to determine the dependent data entities at operation.

506 130 502 506 130 In some embodiments, as shown in operation, the systemmay be configured to decommission the data application and each of the dependent data entities. By way of example, the decommission request received at operationmay be associated with the decommissioning of each of the data application and the data entities associated with the data application. In such an embodiment, operationmay refer to a single action (e.g., “one-click”) decommissioning of dependent data entities in the distributed network. In such an embodiment, the present disclosure contemplates that the systemmay leverage any technique, mechanism, etc. (e.g., accessing workflows, application programming interfaces (APIs), etc.) for causing the decommissioning of a plurality of data entities due to their dependency on the decommissioned data application.

508 510 130 130 508 130 130 In other embodiments, as shown in operationsand, the systemmay be configured to decommission the data application and dissociate the identification object from each of the dependent data entities. In some embodiments, the decommission request may only be associated with the data application, such that the data entities may remain operational within the distributed network in the absence of the data application. As such, the systemmay decommission the data application at operationin response to this decommission request. For the data entities, however, the systemmay remove the association (e.g., terminate the link and data dependencies) between the data application and the data entities. In doing so, the systemmay operate to selectively decommission portions of the distributed network.

512 130 130 130 In any embodiment, as shown in operation, the systemmay be configured to expunge the identification object from the distributed network formed of the plurality of data entities. As described above, the identification object may, for example, uniquely identify the example data application within the distributed network. As such, following decommissioning of the data application, the systemmay operate to remove, expunge, or otherwise purge usage of the identification object from the distributed network. In doing so, the systemmay operate to prevent or minimize the security exposure associated with data entities remaining linked to decommissioned data applications.

As will be appreciated by one of ordinary skill in the art, the present disclosure may be embodied as an apparatus (including, for example, a system, a machine, a device, a computer program product, and/or the like), as a method (including, for example, a business process, a computer-implemented process, and/or the like), or as any combination of the foregoing. Accordingly, embodiments of the present disclosure may take the form of an entirely software embodiment (including firmware, resident software, micro-code, and the like), an entirely hardware embodiment, or an embodiment combining software and hardware aspects that may generally be referred to herein as a “system.” Furthermore, embodiments of the present disclosure may take the form of a computer program product that includes a computer-readable storage medium having computer-executable program code portions stored therein. As used herein, a processor may be “configured to” perform a certain function in a variety of ways, including, for example, by having one or more special-purpose circuits perform the functions by executing one or more computer-executable program code portions embodied in a computer-readable medium, and/or having one or more application-specific circuits perform the function.

It will be understood that any suitable computer-readable medium may be utilized. The computer-readable medium may include, but is not limited to, a non-transitory computer-readable medium, such as a tangible electronic, magnetic, optical, infrared, electromagnetic, and/or semiconductor system, apparatus, and/or device. For example, in some embodiments, the non-transitory computer-readable medium includes a tangible medium such as a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a compact disc read-only memory (CD-ROM), and/or some other tangible optical and/or magnetic storage device. In other embodiments of the present disclosure, however, the computer-readable medium may be transitory, such as a propagation signal including computer-executable program code portions embodied therein.

It will also be understood that one or more computer-executable program code portions for carrying out the specialized operations of the present disclosure may be required on the specialized computer include object-oriented, scripted, and/or unscripted programming languages, such as, for example, Java, Perl, Smalltalk, C++, SAS, SQL, Python, Objective C, and/or the like. In some embodiments, the one or more computer-executable program code portions for carrying out operations of embodiments of the present disclosure are written in conventional procedural programming languages, such as the “C” programming languages and/or similar programming languages. The computer program code may alternatively or additionally be written in one or more multi-paradigm programming languages, such as, for example, F#.

It will further be understood that some embodiments of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of systems, methods, and/or computer program products. It will be understood that each block included in the flowchart illustrations and/or block diagrams, and combinations of blocks included in the flowchart illustrations and/or block diagrams, may be implemented by one or more computer-executable program code portions. These computer-executable program code portions execute via the processor of the computer and/or other programmable data processing apparatus and create mechanisms for implementing the steps and/or functions represented by the flowchart(s) and/or block diagram block(s).

It will also be understood that the one or more computer-executable program code portions may be stored in a transitory or non-transitory computer-readable medium (e.g., a memory, and the like) that may direct a computer and/or other programmable data processing apparatus to function in a particular manner, such that the computer-executable program code portions stored in the computer-readable medium produce an article of manufacture, including instruction mechanisms which implement the steps and/or functions specified in the flowchart(s) and/or block diagram block(s).

The one or more computer-executable program code portions may also be loaded onto a computer and/or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer and/or other programmable apparatus. In some embodiments, this produces a computer-implemented process such that the one or more computer-executable program code portions which execute on the computer and/or other programmable apparatus provide operational steps to implement the steps specified in the flowchart(s) and/or the functions specified in the block diagram block(s). Alternatively, computer-implemented steps may be combined with operator and/or human-implemented steps in order to carry out an embodiment of the present disclosure.

While certain exemplary embodiments have been described and shown in the accompanying drawings, it is to be understood that such embodiments are merely illustrative of, and not restrictive on, the broad disclosure, and that this disclosure not be limited to the specific constructions and arrangements shown and described, since various other changes, combinations, omissions, modifications and substitutions, in addition to those set forth in the above paragraphs, are possible. Those skilled in the art will appreciate that various adaptations and modifications of the just described embodiments may be configured without departing from the scope and spirit of the disclosure. Therefore, it is to be understood that, within the scope of the appended claims, the disclosure may be practiced other than as specifically described herein.